Nonparametric Predictive Inference for Discrete Lifetime Data

This paper presents nonparametric predictive inference for discrete lifetime data. While lifetimes are mostly treated as continuous random variables in statistics, there are scenarios where time observations are recorded as discrete values, for example, in actuary, where lifetimes are often recorded as integers in years. The presented method provides lower and upper probabilities for a variety of events of interest involving discrete lifetimes, with examples provided for illustration. Furthermore, the discrete-time situation is considered for inference of the reliability of systems, with discrete-time data for components of different types and using the survival signature to combine inference on components’ reliability to quantify the overall system reliability.

Authors

Institutions

Publication Details

Journal
Mathematics
Published
2024-11-11
DOI
https://doi.org/10.3390/math12223514
Citations
1
Primary Topic
Statistical Methods and Inference
Type
article
Field-Weighted Citation Impact
0.71
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Nonparametric Predictive Inference for Discrete Lifetime Data

Ali M. Mahnashi, Frank P. A. Coolen, Tahani Coolen-Maturi
1 citations
Mathematics
Statistical Methods and Inference
0.71
article

Nonparametric Predictive Inference for Discrete Lifetime Data

Ali M. Mahnashi, Frank P. A. Coolen, Tahani Coolen-Maturi
article en
1 citations

Abstract

This paper presents nonparametric predictive inference for discrete lifetime data. While lifetimes are mostly treated as continuous random variables in statistics, there are scenarios where time observations are recorded as discrete values, for example, in actuary, where lifetimes are often recorded as integers in years. The presented method provides lower and upper probabilities for a variety of events of interest involving discrete lifetimes, with examples provided for illustration. Furthermore, the discrete-time situation is considered for inference of the reliability of systems, with discrete-time data for components of different types and using the survival signature to combine inference on components’ reliability to quantify the overall system reliability.

MathematicsVol. 12(22)
Durham University (GB), Jazan University (SA)
Openalex Percentile: Top 25%
Statistical Methods and Inference
0.71
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.